Currently, when consumers see a product that interests them, they may have to make an effort to find out more about the product, such as the price of the product and which merchant sells the product. For example, if a consumer sees someone on the street wearing a nondescript jacket and wishes to identify and find out more about the jacket, they have to search the Internet using some descriptive keywords. However, this process may not be straightforward as there is a need for the user to think up the descriptive keywords, which can be difficult for some products, e.g. a nondescript black jacket.
If the consumer is able to identify the product and wishes to purchase the product, he/she needs to visit the merchant's shop or visit the merchant's online web-store. There is currently no single platform that combines both product identification (at any location) and purchasing of the identified products (at any time).
Currently, computer-implemented image recognition techniques may be used to identify products. However, these techniques are not 100% accurate due in part to errors occurring during the image recognition process.
Also, even if a product has a physical tag with a description of the product, consumers may be reluctant to read the description printed on the tag. For example, if a consumer sees someone on the street wearing a nondescript jacket and wishes to identify and find out more about the jacket, the consumer is unlikely to approach the owner of the jacket and ask for permission to read the tag.
A need therefore exists to provide systems and methods for facilitating user identification of a product that seek to address at least some of the above problems.